Quantum - Getting started with QPUs Notebooks

Learn how to set up a Quantum QPUs Notebook

Warning

Some links on this documentation refer to the AI and Machine Learning solution. Quantum computing shares the same infrastructure as a service so you might be redirected to another section of this documentation.

Introduction

A Notebook is a document that integrates code, rich text elements, and multimedia, making it a convenient tool for quantum analysis and visualization.

OVHcloud Quantum QPUs is our managed solution for Jupyter and VS Code Notebooks designed to run jobs on a real Quantum Processing Unit. The notebook still works similarly to an OVHcloud Quantum Emulators notebook, but with a managed token to access a remote QPU. Additional fees will be calculated for the use of this QPU.

Objective

This guide demonstrates how to create, configure, access, stop, restart, and delete a Quantum QPUs Notebook from the OVHcloud Console (UI). This method is user-friendly and ideal for beginners.

Alternatively, you can use one of the following methods:

The Quantum API
The ovhai command-line interface (CLI)
The ovhai Python SDK

Each method offers its distinct advantages, depending on your expertise and preferred workflow.

Requirements

A Public Cloud project in your OVHcloud account.
A Public Cloud user with the Administrator or Quantum Operator & ObjectStore operator roles.

OVHcloud Console Access

Direct link:
Navigation path: Public Cloud > Select your project > Quantum > QPUs

Instructions

OVHcloud Quantum Solutions authorization process

If you're using the API, CLI, or SDK, you will need to complete an authorization process before creating a Quantum QPUs Notebook. To do so, click QPUs under Quantum in the left-hand menu of your Public Cloud project: if the Authorise this project for AI services banner is displayed, click Authorise the project.

Launch your first Quantum Notebook

To create a Quantum Notebook, follow these steps:

OVHcloud Console

AI Solution API

ovhai CLI

Python SDK

In the left-hand menu of your Public Cloud project, click QPUs under Quantum.

Click the Create a notebook button. The Create a notebook page opens: specify the configuration of your Quantum Notebook in the sections below. A summary of your configuration and its estimated price per hour is displayed on the right-hand side.

Name

Give a name to your notebook. This will make it easier to manage when you have multiple Quantum Notebooks created.

Region

Next, select a region.

QPU

Choose the QPU (quantum processor) your notebook will run on.

Flavor

Select the hardware your notebook runs on (CPU or GPU flavor) in the Flavor table, then adjust the Quantity of resources, depending on your needs.

Framework

Choose the Quantum Python framework you want to use, which will be pre-installed and ready to use when your notebook is launched. Select the Version that suits your needs.

Editor

Choose the code editor you want.

Privacy

Then, select your privacy settings: Private (access requires a token) or Public (access without a token).

Warning

Public access will expose your data and code to anyone getting the Quantum Notebook link. Be careful not to use it with sensitive data. On the other hand, Private access will require a user and password combination or a Quantum token to access the Notebook content to ensure a secure environment.

Expiration

The notebook is automatically stopped after 7 consecutive days of operation; your configuration and data are saved. You can turn on Automatically restart after timeout.

Advanced configuration

By default, your Quantum Notebook comes with ephemeral storage (local storage). But in this section, you can also link Object Storage containers (Volumes) and Git repositories (Git Public) to your notebook to easily access your remote data, and add Labels.

If you want to learn more about configuring containers and Git repositories in the Notebook, you can refer to this AI & Machine learning documentation. For now, we will launch a classic Notebook without any external volumes added to it.

SSH key (optional) allows you to access your Notebook remotely.

Launch the Quantum Notebook

At the end of the process, review the summary of your settings and click the Create the notebook button to confirm and launch the creation of your Notebook.

Info

Click CLI equivalent to display the equivalent ovhai CLI command. This command allows you to run the exact same Notebook using the CLI.

When your Notebook is created, it will appear in the list of your Quantum QPUs notebooks.

Create a bearer token from the ovhai CLI. For more detailed instructions on creating a token, check the manage access tokens documentation.
Navigate to the desired region and follow the instructions to create a Quantum Notebook.

GRA AI Solution API, for Gravelines, France.
BHS AI Solution API, for Beauharnois, Canada.

Submit a new notebook POST method

Warning

Make sure to select Bearer Auth instead of OAuth 2.0, which is selected by default.

Create a Notebook API token authentication

Warning

Alpha version warning: This package is currently in the alpha phase of development. The APIs and functionalities of the package may not be fully tested.

Create a bearer token from the ovhai CLI. For more detailed instructions on creating a token, check the manage access tokens documentation.
Install the ovhai Python SDK and follow the instructions in the ovhai PyPI page to create a Quantum Notebook.
Finally, open your terminal and run pip install ovhai.

Here is a basic example of how to do it, making it easy for you to get started:

from ovhai import AuthenticatedClient
from ovhai.api.notebook import notebook_new
from ovhai.models import NotebookSpec, Notebook
from ovhai.ovhai_types import Response

client = AuthenticatedClient(
base_url="https://bhs.ai.cloud.ovh.net",
token="YOUR_QUANTUM_TOKEN",
)

# Define notebook parameters
editor_id = "jupyterlab"
framework_id = "pasqal-qpu"
framework_version = "1.6.2-py312-cpu"
framework_qpu_flavor_id = "orion-beta"
nb_cpu = 1

# Create the notebook creation request
notebook_specs = {
"env": {"editorId": editor_id, "frameworkId": framework_id, "frameworkVersion": framework_version},
"quantumResources": {"qpuFlavorId": framework_qpu_flavor_id},
"resources": {"cpu": nb_cpu},
}

with client as client:
response: Response[Notebook] = notebook_new.sync_detailed(
client=client, body=NotebookSpec.from_dict(notebook_specs)
)

import json
response_content = response.content.decode('utf-8')  # Decode bytes to a string
response_dict = json.loads(response_content)

status_code = response.status_code
id_ = response_dict['id']
spec = response_dict['spec']
status = response_dict['status']
state = status['state']
info = status['info']
url = response_dict['status']['url']

print(f"Status code: {status_code}")
print(f"ID: {id_}")
print(f"Spec: {spec}")
print(f"State: {state}")
print(f"Info: {info}")
print(f"URL: {url}")

Once your Quantum Notebook is created and running, you can access it using the Open JupyterLab button of the notebook page or through the ovhai CLI, Quantum API, or Python SDK.

OVHcloud Console

Quantum API

ovhai CLI

Python SDK

In the left-hand menu of your Public Cloud project, click QPUs under Quantum. Then, click the name of the notebook to open its Overview tab.

In the Connection details card, click the Open JupyterLab button (the button is named after the editor you selected).

On the Notebook page, you will find information about the Notebook, including specifications, life cycle, and attached data, as well as a monitoring link (Monitoring Grafana) for real-time metrics.

Run the following code to list all Quantum Notebooks:

from ovhai import AuthenticatedClient
from ovhai.api.notebook import notebook_get_all
from ovhai.models import NotebookList
from ovhai.ovhai_types import Response

from ovhai import AuthenticatedClient

client = AuthenticatedClient(
base_url="https://bhs.ai.cloud.ovh.net",
token="YOUR_QUANTUM_TOKEN",
)

with client as client:
response: Response[NotebookList] = notebook_get_all.sync_detailed(client=client)
import json
response = json.loads(response.content.decode())
for notebook_info in response["items"]:
print(f"ID: {notebook_info['id']}")
print(f"Name: {notebook_info['spec']['name']}")
print(f"Status: {notebook_info['status']['state']}")
print(f"Framework: {notebook_info['spec']['env']['frameworkId']}")
print(f"Framework version: {notebook_info['spec']['env']['frameworkVersion']}")
print(f"Editor: {notebook_info['spec']['env']['editorId']}")
print(f"Access link: {notebook_info['status']['url']}")
print("---------------")

You can also get Notebook information with this code sample:

from ovhai.api.notebook import notebook_get
from ovhai import AuthenticatedClient
import json

client = AuthenticatedClient(
base_url="https://bhs.ai.cloud.ovh.net",
token="YOUR_QUANTUM_TOKEN",
)
id = "YOUR_NOTEBOOK_UUID"

with client as client:
response = notebook_get.sync_detailed(
id=id, client=client
)

print(json.loads(response.content.decode()))

To connect to your Quantum Notebook, you'll need to authenticate using a username and password combination or an access token.

Using a Username and Password

Enter your Public Cloud project user's credentials to log in to your Quantum Notebook.

Using an Access Token

Click the Login with token button and enter your access token to log in to your Quantum Notebook.

Stopping a Quantum Notebook

You can stop your Quantum Notebook at any time to release its compute resources. This will release its compute resources but will keep your Notebook data and installed libraries. Therefore, you will not incur any further charges for compute unless you restart the Notebook. However, attached storage will be billed at the price of OVHcloud Object Storage (consult the Quantum Notebooks Billing documentation for more information). To do so, follow these steps:

OVHcloud Console

Quantum API

ovhai CLI

Python SDK

In the QPUs list (under Quantum in the left-hand menu of your Public Cloud project), click the ... button next to the Notebook, then Stop. You can also click Stop in the General information card of the notebook. Confirm with Stop.

Use the notebook_stop method to stop the Notebook.

from ovhai.api.notebook import notebook_stop
from ovhai import AuthenticatedClient
client = AuthenticatedClient(
base_url="https://bhs.ai.cloud.ovh.net",
token="YOUR_QUANTUM_TOKEN",
)
id = "YOUR_NOTEBOOK_UUID"

with client as client:
response = notebook_stop.sync_detailed(client=client, id=id)

To restart a stopped Notebook, follow these steps:

OVHcloud Console

Quantum API

ovhai CLI

Python SDK

In the QPUs list (under Quantum in the left-hand menu of your Public Cloud project), click the ... button next to the Notebook, then Start. You can also click Start in the General information card of the notebook. Confirm with Start.

Use the notebook_start method to restart the Notebook.

from ovhai.api.notebook import notebook_start
from ovhai import AuthenticatedClient
client = AuthenticatedClient(
base_url="https://gra.ai.cloud.ovh.net",
token="YOUR_QUANTUM_TOKEN",
)
id = "YOUR_NOTEBOOK_UUID"

with client as client:
response = notebook_start.sync_detailed(
id=id, client=client
)

The notebook must be stopped before deleting it. To delete a Notebook, follow these steps:

OVHcloud Console

Quantum API

ovhai CLI

Python SDK

In the QPUs list (under Quantum in the left-hand menu of your Public Cloud project), click the ... button next to the Notebook, then Delete. You can also click Delete notebook in the General information card of the notebook. Confirm with Delete.

Use the notebook_delete method to delete the Notebook.

from ovhai.api.notebook import notebook_delete
from ovhai import AuthenticatedClient

client = AuthenticatedClient(
base_url="https://gra.ai.cloud.ovh.net",
token="YOUR_QUANTUM_TOKEN",
)
id = "YOUR_NOTEBOOK_UUID"

with client as client:
response = notebook_delete.sync_detailed(
id=id, client=client, force=False
)

print(response.content.decode())

Discover how to access your Object Storage data and Git repositories from your Notebooks using the UI here.
Learn about the technical features, capabilities, and limitations of the Public Cloud Quantum Notebooks offering here.
Get some hints on how to debug your Notebooks if things go wrong here.

For training or technical assistance implementing our solutions, contact your sales representative or visit our Professional Services page to request a quote and have your project analysed by our experts.

Feedback

We would love to help answer questions and appreciate any feedback you may have.

Please send us your questions, feedback, and suggestions regarding Quantum Notebooks:

In the #quantum-computing channel of the OVHcloud Discord server.

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